Variable weight mixed-norm LMS-LMF adaptive algorithm

Author

Aboulnasr, Tyseer ; Zerguine, Azzedine

Author_Institution

Sch. of Inf. Technol. & Eng., Ottawa Univ., Ont., Canada

Volume

1

fYear

1999

Firstpage

791

Abstract

In this paper, we propose a new mixed norm LMS-LMF adaptive algorithm. The algorithm minimizes an objective function defined as a weighted sum of the least mean fourth (LMF) and least mean square (LMS) cost functions. The weighting factor is time varying and adapts itself so as to emphasize one cost function over the other based on proximity to the optimum. Improved convergence is illustrated by examples. Bounds on the step size to ensure mean convergence are also derived.

Keywords

adaptive filters; adaptive signal processing; convergence of numerical methods; filtering theory; least mean squares methods; minimisation; time-varying filters; LMF cost function; LMS cost function; LMS-LMF adaptive algorithm; adaptive filter; convergence; least mean fourth algorithm; least mean square algorithm; objective function minimisation; step size bounds; time varying mixed-norm algorithm; weighting factor; Adaptive algorithm; Adaptive filters; Convergence; Cost function; Equations; Filtering algorithms; Gaussian noise; Information technology; Least squares approximation; Physics;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on

ISSN

1058-6393

Print_ISBN

0-7803-5700-0

Type

conf

DOI

10.1109/ACSSC.1999.832437

Filename

832437